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A Cloud Guru
This course is designed to teach you the new services and tools you can use in AWS to build data analytics applications, as well as build and manage the lifecycle of collecting, storing, processing, and visualizing your data. Data is growing for organizations at an alarming rate, and that means there is a growing need for engineers who know how to gather insight from that data. That is where the AWS Data Analytics - Specialty certification fits into the picture. This certification validates a deep understanding of AWS data analytics services and how they integrate with each other. Once you have passed the exam, you should be able to explain how AWS data analytics services fit into the data lifecycle and answer important questions about what your organization's data is providing. In this course, we cover major tools, topics, and services needed for a successful data analytics pipeline to help you gain hands-on experience and pass the exam. So when you’re ready, join us in the AWS Data Analytics - Specialty course!
Register for this course and see more details by visiting:
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Develops foundational and advanced skills in data analytics for Amazon Web Services (AWS)
Prepares learners for the AWS Certified Data Analytics - Specialty exam
Taught by A Cloud Guru, who are recognized for their expertise in AWS cloud computing
Coursework includes hands-on experience to reinforce learning
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Save AWS Certified Data Analytics - Specialty (DAS-C01) to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in AWS Certified Data Analytics - Specialty (DAS-C01) with these
activities:
Refresher: SQL Fundamentals for Data Manipulation and Analysis
Show steps
Strengthen your foundation in SQL, a crucial skill for data analytics, by reviewing fundamental concepts and practicing data manipulation and analysis techniques.
Browse courses on
SQL
Show steps
-
Revisit basic SQL syntax and data types.
-
Practice writing SQL queries for data selection, filtering, and aggregation.
-
Review advanced SQL concepts such as joins, subqueries, and window functions.
Identify Mentors: Seek Guidance from Experienced Data Analytics Professionals
Show steps
Enhance your learning journey by seeking guidance from experienced data analytics professionals who can provide valuable insights, support, and career advice.
Browse courses on
Mentorship
Show steps
-
Reach out to individuals in your professional network or online platforms like LinkedIn.
-
Attend industry events and conferences to connect with potential mentors.
-
Clearly define your mentorship goals and expectations.
-
Schedule regular meetings with your mentor to discuss progress and receive feedback.
Knowledge Compilation: Resources and Tools for AWS Data Analytics
Show steps
Expand your repository of AWS data analytics knowledge by compiling a comprehensive list of relevant resources, tools, and best practices.
Show steps
-
Explore AWS documentation, blogs, and forums for resources on data analytics.
-
Identify third-party tools and services that complement AWS data analytics offerings.
-
Categorize and organize the resources based on their purpose and relevance.
-
Share your compilation with others to contribute to the community of AWS data analytics learners.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Study Group: Discussing and Analyzing AWS Data Analytics Services
Show steps
Engage in collaborative learning by joining a study group where you can discuss concepts, ask questions, and share insights related to AWS data analytics services.
Show steps
-
Find or form a study group with other learners taking the AWS Data Analytics course.
-
Establish a regular meeting schedule and set goals for each session.
-
Prepare discussion topics and materials based on the course content.
-
Engage in active discussions, sharing perspectives and fostering a collaborative learning environment.
Tutorial: Delving into Data Analytics with AWS Services
Show steps
Empower your understanding of AWS data analytics capabilities by following guided tutorials that demonstrate how these services work together.
Show steps
-
Identify relevant tutorial resources from the AWS documentation or third-party sources.
-
Review the tutorial content and follow the provided instructions.
-
Experiment with the AWS services covered in the tutorials to gain hands-on experience.
Hands-on Exercises: Data Collection and Storage in AWS
Show steps
Solidify your knowledge of data collection and storage practices in AWS by engaging in repetitive exercises that simulate real-world scenarios.
Browse courses on
Data Collection
Show steps
-
Set up AWS resources, including S3 buckets and DynamoDB tables.
-
Practice loading data into S3 using various methods, such as direct upload and AWS CLI.
-
Design and implement DynamoDB tables for storing structured data.
-
Explore additional AWS services for data collection and storage, such as Kinesis and Redshift.
AWS Summit: Data Analytics Track
Show steps
Immerse yourself in the latest advancements in AWS data analytics by attending the Data Analytics track at an AWS Summit, where you can learn from experts, engage with peers, and explore hands-on workshops.
Browse courses on
Data Analytics
Show steps
-
Register for the AWS Summit and select the Data Analytics track.
-
Attend sessions and workshops led by industry experts.
-
Network with professionals in the field of data analytics.
-
Participate in hands-on labs to gain practical experience with AWS data analytics services.
Project: Building a Data Analytics Pipeline for a Real-world Case Study
Show steps
Demonstrate your mastery of data analytics concepts by building a comprehensive data analytics pipeline from scratch, addressing a specific business or research case study.
Browse courses on
Case study
Show steps
-
Identify a suitable case study and define the problem statement.
-
Design the data analytics pipeline, including data sources, processing steps, and visualization techniques.
-
Implement the pipeline using appropriate AWS services, such as Glue, Athena, and QuickSight.
-
Analyze the results and draw meaningful insights from the processed data.
-
Document and present your findings in a report or presentation.
Refresher: SQL Fundamentals for Data Manipulation and Analysis
Show steps
Strengthen your foundation in SQL, a crucial skill for data analytics, by reviewing fundamental concepts and practicing data manipulation and analysis techniques.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Revisit basic SQL syntax and data types.
- Practice writing SQL queries for data selection, filtering, and aggregation.
- Review advanced SQL concepts such as joins, subqueries, and window functions.
Identify Mentors: Seek Guidance from Experienced Data Analytics Professionals
Show steps
Enhance your learning journey by seeking guidance from experienced data analytics professionals who can provide valuable insights, support, and career advice.
Browse courses on
Mentorship
Show steps
Show steps
Show steps
- Reach out to individuals in your professional network or online platforms like LinkedIn.
- Attend industry events and conferences to connect with potential mentors.
- Clearly define your mentorship goals and expectations.
- Schedule regular meetings with your mentor to discuss progress and receive feedback.
Knowledge Compilation: Resources and Tools for AWS Data Analytics
Show steps
Expand your repository of AWS data analytics knowledge by compiling a comprehensive list of relevant resources, tools, and best practices.
Show steps
Show steps
Show steps
- Explore AWS documentation, blogs, and forums for resources on data analytics.
- Identify third-party tools and services that complement AWS data analytics offerings.
- Categorize and organize the resources based on their purpose and relevance.
- Share your compilation with others to contribute to the community of AWS data analytics learners.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Study Group: Discussing and Analyzing AWS Data Analytics Services
Show steps
Engage in collaborative learning by joining a study group where you can discuss concepts, ask questions, and share insights related to AWS data analytics services.
Show steps
Show steps
Show steps
- Find or form a study group with other learners taking the AWS Data Analytics course.
- Establish a regular meeting schedule and set goals for each session.
- Prepare discussion topics and materials based on the course content.
- Engage in active discussions, sharing perspectives and fostering a collaborative learning environment.
Tutorial: Delving into Data Analytics with AWS Services
Show steps
Empower your understanding of AWS data analytics capabilities by following guided tutorials that demonstrate how these services work together.
Show steps
Show steps
Show steps
- Identify relevant tutorial resources from the AWS documentation or third-party sources.
- Review the tutorial content and follow the provided instructions.
- Experiment with the AWS services covered in the tutorials to gain hands-on experience.
Hands-on Exercises: Data Collection and Storage in AWS
Show steps
Solidify your knowledge of data collection and storage practices in AWS by engaging in repetitive exercises that simulate real-world scenarios.
Browse courses on
Data Collection
Show steps
Show steps
Show steps
- Set up AWS resources, including S3 buckets and DynamoDB tables.
- Practice loading data into S3 using various methods, such as direct upload and AWS CLI.
- Design and implement DynamoDB tables for storing structured data.
- Explore additional AWS services for data collection and storage, such as Kinesis and Redshift.
AWS Summit: Data Analytics Track
Show steps
Immerse yourself in the latest advancements in AWS data analytics by attending the Data Analytics track at an AWS Summit, where you can learn from experts, engage with peers, and explore hands-on workshops.
Browse courses on
Data Analytics
Show steps
Show steps
Show steps
- Register for the AWS Summit and select the Data Analytics track.
- Attend sessions and workshops led by industry experts.
- Network with professionals in the field of data analytics.
- Participate in hands-on labs to gain practical experience with AWS data analytics services.
Project: Building a Data Analytics Pipeline for a Real-world Case Study
Show steps
Demonstrate your mastery of data analytics concepts by building a comprehensive data analytics pipeline from scratch, addressing a specific business or research case study.
Browse courses on
Case study
Show steps
Show steps
Show steps
- Identify a suitable case study and define the problem statement.
- Design the data analytics pipeline, including data sources, processing steps, and visualization techniques.
- Implement the pipeline using appropriate AWS services, such as Glue, Athena, and QuickSight.
- Analyze the results and draw meaningful insights from the processed data.
- Document and present your findings in a report or presentation.
Career center
Learners who complete AWS Certified Data Analytics - Specialty (DAS-C01) will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst is a professional who is responsible for collecting, cleaning, and analyzing data to identify trends and patterns that can be used to make better business decisions. This course can help you develop the skills you need to become a successful Data Analyst, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Data Analyst, you would use this knowledge to develop insights that can help improve your organization's bottom line.
Data Scientist
Data Scientist
A Data Scientist is a professional who uses data to solve business problems. This course can help you develop the skills you need to become a successful Data Scientist, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Data Scientist, you would use this knowledge to develop models and algorithms that can help improve your organization's decision-making process.
Data Engineer
Data Engineer
A Data Engineer is a professional who is responsible for designing, building, and maintaining data pipelines and infrastructure. This course can help you develop the skills you need to become a successful Data Engineer, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Data Engineer, you would use this knowledge to ensure that your organization's data is available and accessible to the people who need it.
Data Architect
Data Architect
A Data Architect is a professional who is responsible for designing and managing data systems. This course can help you develop the skills you need to become a successful Data Architect, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Data Architect, you would use this knowledge to ensure that your organization's data is organized and accessible in a way that meets the needs of the business.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer is a professional who uses machine learning to solve business problems. This course can help you develop the skills you need to become a successful Machine Learning Engineer, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Machine Learning Engineer, you would use this knowledge to develop and deploy machine learning models that can help improve your organization's decision-making process.
Business Analyst
Business Analyst
A Business Analyst is a professional who is responsible for understanding the business needs of an organization and translating those needs into technical requirements. This course can help you develop the skills you need to become a successful Business Analyst, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Business Analyst, you would use this knowledge to help your organization make better decisions about how to use data.
Compliance Analyst
Compliance Analyst
A Compliance Analyst is a professional who is responsible for ensuring that an organization complies with all applicable laws and regulations. This course can help you develop the skills you need to become a successful Compliance Analyst, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Compliance Analyst, you would use this knowledge to help your organization identify and mitigate risks that could lead to non-compliance with applicable laws and regulations.
Sales Analyst
Sales Analyst
A Sales Analyst is a professional who is responsible for understanding the sales needs of an organization and developing and implementing sales strategies. This course can help you develop the skills you need to become a successful Sales Analyst, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Sales Analyst, you would use this knowledge to help your organization develop and execute sales strategies that are effective and efficient.
Financial Analyst
Financial Analyst
A Financial Analyst is a professional who is responsible for understanding the financial needs of an organization and developing and implementing financial strategies. This course can help you develop the skills you need to become a successful Financial Analyst, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Financial Analyst, you would use this knowledge to help your organization develop and execute financial strategies that are effective and efficient.
Marketing Analyst
Marketing Analyst
A Marketing Analyst is a professional who is responsible for understanding the marketing needs of an organization and developing and implementing marketing campaigns. This course can help you develop the skills you need to become a successful Marketing Analyst, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Marketing Analyst, you would use this knowledge to help your organization develop and execute marketing campaigns that are effective and efficient.
Risk Analyst
Risk Analyst
A Risk Analyst is a professional who is responsible for understanding the risks that an organization faces and developing and implementing strategies to mitigate those risks. This course can help you develop the skills you need to become a successful Risk Analyst, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Risk Analyst, you would use this knowledge to help your organization identify and mitigate risks that could negatively impact the organization.
Product Manager
Product Manager
A Product Manager is a professional who is responsible for managing the development and launch of new products. This course can help you develop the skills you need to become a successful Product Manager, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Product Manager, you would use this knowledge to make decisions about which products to develop, how to market those products, and how to price those products.
Auditor
Auditor
An Auditor is a professional who is responsible for examining an organization's financial records and operations to ensure that they are accurate and compliant with applicable laws and regulations. This course can help you develop the skills you need to become a successful Auditor, including how to use AWS data analytics services to collect, store, process, and visualize data. As an Auditor, you would use this knowledge to help your organization identify and mitigate risks that could lead to financial or operational losses.
Data Journalist
Data Journalist
A Data Journalist is a professional who uses data to tell stories and inform the public about important issues. This course can help you develop the skills you need to become a successful Data Journalist, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Data Journalist, you would use this knowledge to create data-driven stories that can inform and educate the public.
Consultant
Consultant
A Consultant is a professional who provides advice and guidance to organizations on a variety of topics, including data analytics. This course can help you develop the skills you need to become a successful Consultant, including how to use AWS data analytics services to collect, store, process, and visualize data. As a Consultant, you would use this knowledge to help your clients make better decisions about how to use data to improve their business.
For more career information including salaries, visit:
OpenCourser.com/course/axalyz/aws
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
AWS Certified Data Analytics - Specialty (DAS-C01).
Covers the fundamentals of machine learning from a probabilistic perspective. It provides a comprehensive overview of the field and how to use machine learning to solve real-world problems. This book is commonly used as a textbook at academic institutions or by industry professionals.
Covers the fundamentals of natural language processing (NLP) with Python. It provides a comprehensive overview of the field and how to use NLP to solve real-world problems. This book is commonly used as a textbook at academic institutions or by industry professionals.
Covers the fundamentals of computer vision with Python. It provides a comprehensive overview of the field and how to use computer vision to solve real-world problems. This book is commonly used as a textbook at academic institutions or by industry professionals.
Covers the fundamentals of data manipulation with Python. It provides a comprehensive overview of the field and how to use Python to solve real-world problems. This book is commonly used as a textbook at academic institutions or by industry professionals.
Save
Covers the fundamentals of data mining. It provides a comprehensive overview of the field and how to use data mining to solve real-world problems. This book is commonly used as a textbook at academic institutions or by industry professionals.
Covers the fundamentals of data visualization with Python. It provides a comprehensive overview of the field and how to use data visualization to solve real-world problems. This book is commonly used as a textbook at academic institutions or by industry professionals.
Provides a theoretical foundation for data analytics in the cloud, covering topics such as data modeling, query processing, and machine learning. It good resource for those who want to understand the underlying principles of data analytics or who are working on complex data analytics projects.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/axalyz/aws
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Time
870 hours
Level
Graduate
Via
Pluralsight
Instructor
A Cloud Guru
Language
English
Good to know
Develops foundational and advanced skills in data analytics for Amazon Web Services (AWS)
Prepares learners for the AWS Certified Data Analytics - Specialty exam
Taught by A Cloud Guru, who are recognized for their expertise in AWS cloud computing
Coursework includes hands-on experience to reinforce learning
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